CN111239721B - Entropy-solving and speed-ambiguity-solving method for vehicle-mounted MIMO radar - Google Patents
Entropy-solving and speed-ambiguity-solving method for vehicle-mounted MIMO radar Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/583—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/60—Velocity or trajectory determination systems; Sense-of-movement determination systems wherein the transmitter and receiver are mounted on the moving object, e.g. for determining ground speed, drift angle, ground track
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Abstract
The invention discloses a method for solving entropy and speed ambiguity by a vehicle-mounted MIMO radar, which comprises the steps of carrying out ADC processing on measured echo data and rearranging according to a channel sequence; performing FFT (fast Fourier transform) of a distance-Doppler dimension on the echo signal of each channel; constructing 2L groups of different speeds according to the obtained fuzzy speed to obtain 2L groups of new weighting vectors and output power; the speed ambiguity of all signals in the same range-Doppler gate can be solved simultaneously by means of solving the entropy, so that the accurate angle information of all ground clutter signals relative to the radar can be accurately estimated, and finally the non-ambiguity speed of the vehicle can be solved according to the symmetry of the ground clutter in the azimuth direction relative to the advancing direction of the radar.
Description
Technical Field
The invention relates to a vehicle-mounted radar signal processing method, in particular to a method for solving velocity ambiguity by solving entropy of a vehicle-mounted MIMO radar.
Background
The vehicle-mounted GPS speed measurement principle is that specific longitude and latitude coordinates of each second are calculated, then the specific longitude and latitude coordinates are divided by one second to obtain the average speed within one second, namely the average speed of a vehicle in a distance is measured through GPS speed measurement, and in practical application, the calculated data cannot be accurate due to various errors.
The radar speed measurement is that the radar calculates the instantaneous moving speed of a moving object by transmitting high-frequency radio waves and Doppler, namely the radar measures the instantaneous speed. In addition, the speed and distance measuring accuracy of the millimeter wave radar is far higher than that of a visual sensor, and compared with a laser radar, the millimeter wave radar has better penetrating power, is farther in detection distance and has the advantage of being all-weather all day long, so that the millimeter wave radar is widely used as a vehicle-mounted sensor.
Multiple-input multiple-output (MIMO) radar is a technique that improves the angle estimation capability of Frequency Modulated Continuous Wave (FMCW) radar, with multiple TX antennas transmitting to the same set of RX antennas. The signals from multiple TX antennas need to be orthogonal (i.e., should not interfere with each other), MIMO radar is mainly sometimes Time Division Multiplexing (TDM), Code Division Multiplexing (CDM), frequency division multiplexing (CDM). FDM-MIMO adds hardware complexity in the transmit and receive chains, and CDM-MIMO results in computational complexity and reduced performance. Therefore, TDM-MIMO is superior to other methods in providing orthogonality, but since the TDM MIMO waveform is a time interleaved chirped continuous wave (LFMCW) waveform, when the target speed is large enough, it causes an additional phase difference between channels, and eventually causes speed measurement ambiguity.
Some documents currently propose to compensate the phase difference by finding a phase compensation peak, and a method for resolving speed ambiguity of an on-board FMCW radar based on TDM MIMO is proposed in patent CN110412558A, and a doppler ambiguity compensation factor is found by a search method. The speed ambiguity problem of TDM-MIMO is pointed out in patent CN108594233A, and it is proposed to perform phase compensation by comparing the maximum amplitude values after FFT output under multiple compensation coefficients.
Disclosure of Invention
The purpose of the invention is as follows: the problem of radar speed measurement ambiguity is caused when the MIMO radar of the vehicle-mounted TDM system has overlarge movement speed, the number of targets needs to be estimated in a traditional speed ambiguity solving mode, and the algorithm flow is complex and the universality is not strong. The invention aims to provide a method for solving speed ambiguity by entropy calculation of a vehicle-mounted MIMO radar, which is a speed-angle joint estimation method based on information entropy and ground clutter symmetry and can obtain the unambiguous speed of a vehicle by simple calculation.
The technical scheme is as follows: the invention discloses a method for solving entropy and speed ambiguity by a vehicle-mounted MIMO radar, which comprises the following steps:
(1) performing ADC processing on the measured echo data, and rearranging according to a channel sequence;
(2) performing range-Doppler FFT (fast Fourier transform) on the echo signal of each channel to obtain a range-Doppler fuzzy graph and a frequency domain signal; calculating to obtain a fuzzy speed, namely a radial speed;
(3) constructing 2L groups of different speeds according to the obtained fuzzy speed to obtain 2L groups of new weighting vectors w and output power P'DBF；
(4) Comparing to obtain the group number e of the minimum entropy value in the 2L groups of output power, and reversely deducing the unambiguous radial velocity v of the ground clutter relative to the radartrue(e) And a weighting vector w (e);
(5) two symmetrical ground clutter under the same range-Doppler gate are taken, and DBF is carried out through w (e) to obtain angle information;
(6) and solving the non-fuzzy speed of the vehicle according to the symmetry of the ground clutter in the azimuth direction about the normal line of the radar.
The solving method of the invention further comprises the following steps:
step 1, the speed V of a vehicle provided with the MIMO radaryWhen driving straight ahead, the ground clutter at the same angle to the heading has the same radial velocity relative to the radar, so that within the same range-doppler gate there will be a set of ground clutter symmetrical about the heading.
And 2, the vehicle-mounted MIMO radar comprises M transmitting antennas and N receiving antennas, the M transmitting antennas and the N receiving antennas can be equivalent to MN channels, the distance between the transmitting antennas is d1, the distance between the receiving antennas is d2, the equivalent distance between the transmitting antennas and the receiving antennas is d, in order to ensure that the transmitting waveforms have good orthogonality, waveform configuration is carried out at a transmitting end in a time division multiple access (TDM) mode, the transmitting antennas are sequentially opened according to the sequence of 1, 2, … … and M, and the N receiving antennas simultaneously receive echo signals generated by each transmitting antenna.
Step 3, carrying out ADC processing on the received echo signals to obtain
Wherein, i is 1: n _ chirp represents a slow time sampling sequence number, and n _ chirp is a pulse number; k is 1: n _ samples represents the number of fast time sampling points, and n _ samples is the number of the fast time sampling points; mn is 1: MN represents the channel serial number, MN is the equivalent channel number, in addition, because the chip interior has already carried out the processing of understanding the linear frequency modulation (dechirp) to the signal, here the echo signal has already been the intermediate frequency signal, can directly carry on subsequent signal processing. Wherein, 1: MN stands for 1, 2, 3, 4, 5.
Step 4, due to the TDM transmitting waveform configuration mode, the echo signals of MN channels need to be processed according to the transmitting antenna starting sequence at the receiving end
Re-ordering to Smn＝[S11、S12、……、S1n，S21、……S2n，……，Sm1、……SMN]Firstly, N is made for the sorted echo signals in the distance dimensionrFourier Transform (FFT) of the points, then M in the velocity dimensiondFourier Transform (FFT) of points to obtain range-Doppler dimension fuzzy graph and frequency domain signal Smn(nr，ma) Wherein n isr＝1：Nr，md＝1：Md。
Step 5, selecting echo signals S under the same range-Doppler gatemn(rp，dp) Analysis, wherein 1. ltoreq. rp≤Nr，1≤dp≤MdAccording to the Doppler gate dpThe instantaneous speed V of the ground clutter relative to the radar can be calculatedest(p)＝dp×vres(wherein, velocity resolution
TcTime of operation for each transmit antenna, λ is wavelength); the instantaneous velocity here is the radial velocity.
Step 6, in practical application, because a mode of configuring a transmitting waveform by Time Division Multiplexing (TDM) is adopted, when the speed of the vehicle-mounted radar is high, extra phase difference is generated among channels due to the time difference of opening of a transmitting antenna
Ultimately leading to speed measurement ambiguity when the estimated radial velocity V of the vehicle relative to ground clutterestIs inaccurate.
Step 7, in order to solve the speed ambiguity, the real speed and angle of the ground clutter relative to the radar are calculated, and the phase difference mentioned in the step 6 needs to be compensated
Here, the
Wherein v istrueTo avoid blurring the velocity, an optimization model can be constructed to solve for the phase difference:vtrue＝vest+jvmaxwherein
j is taken from-L to L with equal step size to obtain 2L different vtrueThen, 2L sets of different compensation phases are corresponded.
Step 8, respectively compensating the 2L groups of compensation phases into the weighting vector a to obtain 2L groups of new weighting vectors
And due to the weighted vector
The new weight vector can be expressed as
And theta is the arrival angle of the target echo.
Step 9, using the new weighting vector w of 2L groups obtained in step 8 for Digital Beam Forming (DBF), obtaining output power P 'of 2L groups'DBFI.e. PDBF(1：2L)＝w(1：2L)RxwH(1: 2L), where H denotes conjugate transpose, covariance matrix
11, according to the group number e corresponding to the minimum entropy value, the unambiguous radial velocity v of the vehicle relative to the ground clutter can be obtained by reverse estimationtrue(e)＝vest+evmaxThereby obtaining the inter-channel phase difference
Compensating the weighted vector to a weighted vector a to obtain an ideal weighted vector
Use of w (e) for Digital Beamforming (DBF) to obtain a set of desired output powers P'DBF(e)＝w(e)RxwH(e) Therefore, the real azimuth angle of a group of symmetrical ground clutter signals relative to the advancing direction of the radar in the same range-Doppler gate can be calculated.
Step 12, since a set of ground clutter A, B symmetric about the heading exists within the same range-doppler gate, and step 11 knows the true azimuth angle of the set of symmetric ground clutter with respect to the radar heading within the same range-doppler gate. Then A, B are known to be v relative to the radar radial velocitytrue(e) The azimuth angles are two signals of-beta and beta respectively, so that the unambiguous speed of the vehicle can be calculated according to the cosine theorem of the triangle
The method can simultaneously solve the speed ambiguity of all signals in the same range-Doppler gate by solving the entropy, thereby accurately estimating the accurate angle information of all ground clutter signals relative to the radar, and finally solving the self non-ambiguity speed of the vehicle according to the symmetry of the ground clutter in the azimuth direction relative to the advancing direction of the radar.
Has the advantages that: and obtaining speed information corresponding to the minimum entropy value by comparing the output power of the beam forming so as to obtain the unambiguous radial speed of the ground clutter relative to the radar, simultaneously calculating the real azimuth angle of a group of ground clutter relative to the radar in the same range-Doppler gate, and finally calculating the unambiguous speed of the vehicle according to the symmetry of the ground clutter relative to the advancing direction of the radar in the same range-Doppler gate.
Drawings
FIG. 1 is a diagram of a practical application scenario of the present invention;
FIG. 2 is a flow chart of entropy solving speed ambiguity of vehicle-mounted MIMO radar;
FIG. 3 is a graph of an angular estimate of a set of symmetric ground clutter according to the present invention.
Detailed Description
The invention is further described below with reference to examples.
The flow chart of entropy-solving and speed-ambiguity-solving for the vehicle-mounted MIMO radar of the embodiment is shown in fig. 2, and the method specifically includes the following steps:
step 1, the speed V of a vehicle provided with the MIMO radaryThe radar has the advantages that when the radar runs towards the right front, ground clutter with the same included angle with the advancing direction has the same radial speed relative to the radar, so that a group of ground clutter symmetrical about the advancing direction exists in the same distance-Doppler gate; as shown in fig. 1.
And 2, the vehicle-mounted MIMO radar comprises M transmitting antennas and N receiving antennas, the M transmitting antennas and the N receiving antennas can be equivalent to MN channels, the distance between the transmitting antennas is d1, the distance between the receiving antennas is d2, the equivalent distance between the transmitting antennas and the receiving antennas is d, in order to ensure that the transmitting waveforms have good orthogonality, waveform configuration is carried out at a transmitting end in a time division multiple access (TDM) mode, the transmitting antennas are sequentially opened according to the sequence of 1, 2, … … and M, and the N receiving antennas simultaneously receive echo signals generated by each transmitting antenna.
Step 3, carrying out ADC processing on the received echo signals to obtain
Wherein, i is 1: n _ chirp represents a slow time sampling sequence number, and n _ chirp is a pulse number; k is 1: n _ samples represents the number of fast time sampling points, and n _ samples is the number of the fast time sampling points; mn is 1: MN represents the channel serial number, MN is the equivalent channel number, in addition, because the chip is internally processed with the known linear frequency modulation (dechirp) to the signal, the echo signal is the intermediate frequency signal, and the subsequent signal processing can be directly carried out.
Step 4, because of the TDM transmitting waveform configuration mode, the MN channels need to be processed according to the transmitting antenna starting sequence at the receiving endEcho signal
Re-ordering to Smn＝[S11、S12、……、S1n，S21、……S2n，……，Sm1、……SMN]The ordered echo signals are first processed by N in the distance dimension, Fourier transform (FFT) of points and then M in the velocity dimensiondFourier Transform (FFT) of points to obtain range-Doppler dimension fuzzy graph and frequency domain signal Smn(nr，md) Wherein n isr＝1：Nr，md＝1：Md。
Step 5, selecting echo signals S under the same range-Doppler gatemn(rp，dp) Analysis, wherein 1. ltoreq. rp≤Nr，1≤dp≤MdAccording to the Doppler gate dpThe instantaneous velocity V of the ground clutter relative to the radar can be calculatedest(p)＝dp×vres(wherein, velocity resolution
Tcλ is the wavelength for the time each transmit antenna is operating).
Step 6, in practical application, because a mode of configuring a transmitting waveform by Time Division Multiplexing (TDM) is adopted, when the speed of the vehicle-mounted radar is high, extra phase difference is generated among channels due to the time difference of opening of a transmitting antenna
Finally, speed measurement ambiguity is caused, and the estimated radial speed V of the vehicle relative to the ground clutterestIs inaccurate.
Step 7, in order to solve the speed ambiguity, the real speed and angle of the ground clutter relative to the radar are calculated, and the phase difference mentioned in the step 6 needs to be compensated
Here, the
Wherein v istrueTo avoid blurring the velocity, an optimization model can be constructed to solve for the phase difference: v. oftrue＝vest+jvmaxWherein
j is taken from-L to L in equal steps to obtain 2L different vtrueThen, 2L sets of different compensation phases are corresponded.
Step 8, respectively compensating the 2L groups of compensation phases into the weighting vector a to obtain 2L groups of new weighting vectors
And due to the weighted vector
The new weight vector can be expressed as
And theta is the arrival angle of the target echo.
Step 9, using the new weighting vector w of 2L groups obtained in step 8 for Digital Beam Forming (DBF), obtaining output power P 'of 2L groups'DBFI.e. PDBF(1：2L)＝w(1：2L)RxwH(1: 2L), where H denotes conjugate transpose, covariance matrix
11, according to the group number e corresponding to the minimum entropy value, the unambiguous radial velocity v of the vehicle relative to the ground clutter can be obtained by reverse estimationtrue(e)＝vest+evmaxThereby obtaining the inter-channel phase difference
Compensating the weighted vector to a weighted vector a to obtain an ideal weighted vector
Use of w (e) for Digital Beamforming (DBF) to obtain a set of desired output powers P'DBF(e)＝w(e)RxwH(e) Therefore, the real azimuth angle of a group of symmetrical ground clutter signals relative to the advancing direction of the radar in the same range-Doppler gate can be calculated.
Step 12, since a set of ground clutter A, B symmetric about the heading exists within the same range-doppler gate, and step 11 knows the true azimuth angle of the set of symmetric ground clutter with respect to the radar heading within the same range-doppler gate. Then A, B are known to be v relative to the radar radial velocitytrue(e) The azimuth angles are two signals of-beta and beta respectively, so that the unambiguous speed of the vehicle can be calculated according to the cosine theorem of the triangle
The speed ambiguity resolution and phase compensation angle measurement are carried out on all ground clutter signals in a range-Doppler gate, the range-speed gate is randomly selected, the range-speed gate at the position with stronger ground clutter is selected for convenience of processing, and the method can be better applied to vehicle-mounted radar speed measurement.
Through the steps, the unambiguous speed of the vehicle relative to the ground clutter can be calculated, and the azimuth angles of a group of symmetrical ground clutter relative to the radar in the same range-Doppler gate can be obtained. As shown in fig. 3, before phase compensation, there are multiple high peaks, it is impossible to distinguish which peak corresponds to an azimuth of the ground clutter relative to the radar, and after the entropy is solved to obtain compensation phase compensation to a weighting vector, two symmetrical peak points can be clearly seen, and the corresponding abscissa is an azimuth of a group of symmetrical ground clutter relative to the radar.
Claims (5)
1. A method for solving velocity ambiguity by solving entropy of a vehicle-mounted MIMO radar is characterized by comprising the following steps:
(1) the vehicle-mounted MIMO radar comprises M transmitting antennas and N receiving antennas, and can be equivalently formed into MN channels, and the distance between the transmitting antennas is d1The spacing between the receiving antennas is d2The equivalent spacing of the transmitting and receiving antennas is d, waveform configuration is carried out at a transmitting end in a TDM mode, the transmitting antennas are sequentially opened according to the sequence of 1, 2, 1.·. and M, and N receiving antennas simultaneously receive echo signals generated by each transmitting antenna;
(2) the received echo signal is processed by ADC to obtain
Wherein, i is 1: n _ chirp represents a slow time sampling sequence number, and n _ chirp is a pulse number; k is 1: n _ samples represents the number of fast time sampling points, and n _ samples is the number of the fast time sampling points; mn is 1: MN represents the channel serial number, and MN is the equivalent channel number;
(3) echo signals to MN channels
Re-ordering to Smn＝[S11、S12、......、S1n，S21、......S2n，......，Sm1、......SMN]Firstly, N is made for the sorted echo signals in the distance dimensionrFourier transform of points, and then M in velocity dimensiondFourier transform of points to obtain range-Doppler dimension fuzzy image and frequency domain signal Smn(nr，md) Wherein n isr＝1：Nr，md＝1：Md；
(4) Selecting echo signals S under the same range-Doppler gatemn(rp，dp) Analysis, wherein 1. ltoreq. rp≤Nr，1≤dp≤MdAccording to the Doppler gate dpCalculating the radial velocity V of the ground clutter relative to the radarest(p)＝dp×vers(ii) a Wherein the velocity resolution
Tcλ is the wavelength for the time each transmit antenna is operating;
(5) construction optimization model solution phase difference
vtrue＝vest+jvmax；
j is taken from-L to L in equal steps to obtain 2L different vtrueCorresponding to different compensation phases of the 2L groups, and obtaining new weighting vectors w and output power P 'of the 2L groups'DBF(ii) a Wherein
vtrueTo not obscure the velocity, VestIs the radial velocity;
(6) comparing to obtain the group number e of the minimum entropy value in the 2L groups of output power, and reversely deducing the unambiguous radial velocity v of the ground clutter relative to the radartrue(e) And a weighting vector w (e); two symmetrical ground clutter under the same range-Doppler gate are taken, and DBF is carried out through w (e) to obtain angle information;
(7) and solving the non-fuzzy speed of the vehicle according to the symmetry of the ground clutter in the azimuth direction about the normal line of the radar.
2. According to the rightThe method for solving the speed ambiguity by solving the entropy of the vehicle-mounted MIMO radar according to claim 1 is characterized in that the step (5) specifically comprises the following steps: respectively compensating the 2L groups of compensation phases into a weighting vector a to obtain 2L groups of new weighting vectors
Wherein the weighting vector
The new weight vector can be expressed as
Wherein theta is the arrival angle of the target echo;
then, the obtained new weighting vectors w with different 2L groups are used for digital beam forming to obtain 2L groups with different output power P'DBFI.e. PDBF(1：2L)＝w(1：2L)RxwH(1: 2L), where H denotes conjugate transpose, covariance matrix
3. The method for solving the speed ambiguity by the entropy calculation of the vehicle-mounted MIMO radar according to claim 1, wherein the step (6) is specifically as follows: calculating P'DBFEntropy value En (1: 2L) of (1: 2L) - Σ [ P (1: 2L) log2P(1：2L)]Wherein, in the process,
back comparison of 2L groups P'DBFAnd taking the group number e corresponding to the minimum entropy value, namely En (e) ═ min [ En (1: 2L)]，1≤e≤2L；
According to the group number e corresponding to the minimum entropy value, the unambiguous radial velocity v of the vehicle relative to the ground clutter is obtained by reverse estimationtrue(e)＝vest+evmaxThereby obtaining the inter-channel phase difference
Compensating the weighted vector to a weighted vector a to obtain an ideal weighted vector
Use of w (e) for digital beamforming to obtain a set of desired output powers P'DBF(e)＝w(e)RxwH(e) Therefore, the true azimuth angle of a group of symmetrical ground clutter signals relative to the radar advancing direction in the same range-Doppler gate can be calculated.
4. The method for solving the speed ambiguity by the entropy calculation of the vehicle-mounted MIMO radar according to claim 1, wherein the step (7) is specifically as follows: if a group of ground clutter A, B symmetrical about the radar heading exists within the same range-doppler gate, then, based on the true azimuth angles of the group of symmetrical ground clutter within the same range-doppler gate relative to the radar heading, A, B is all v relative to the radar radial velocitytrue(e) And calculating two signals with azimuth angles of-beta and beta respectively to obtain the unambiguous speed of the vehicle
5. The method for entropy velocity ambiguity resolution of vehicle-mounted MIMO radar according to claim 1, wherein: in step (1), the vehicle equipped with the MIMO radar is driven at a speed VyWhen the vehicle runs towards the right front, the ground clutter with the same included angle with the advancing direction has the same radial speed relative to the radar, and a group of ground clutter symmetrical about the advancing direction exists in the same range-Doppler gate.
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| US6828929B2 (en) * | 2003-01-30 | 2004-12-07 | Raytheon Company | Technique for non-coherent integration of targets with ambiguous velocities |
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| US10627483B2 (en) * | 2016-07-09 | 2020-04-21 | Texas Instruments Incorporated | Methods and apparatus for velocity detection in MIMO radar including velocity ambiguity resolution |
| CN106842166B (en) * | 2017-03-31 | 2019-04-30 | 东南大学 | A kind of solution velocity ambiguity method suitable for LFMCW radar system |
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| CN110412558B (en) * | 2019-07-03 | 2022-05-17 | 南京理工大学 | Method for resolving speed ambiguity of vehicle-mounted FMCW radar based on TDM MIMO |
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